This manuscript introduces a novel framework to extend the accessibility of Twitter users’ timelines to people with disabilities. Our proposed framework is designed with iconic speaker and information functionalities which will enable transcription of multi- media content and provide users the opportunity to read and hear the translated transcripts depending upon the user’s primary language. This work is one of its kind that opens Twitter’s user timeline completely to people with disabilities.

Against the backdrop of the post-pandemic COVID-19, regional short-distance tourism has become more prevalent. This paper used Wuhan Urban Agglomeration (WUA) as the research area and explored spatial structure characteristics and road traffic accessibility issues of A-level tourist attractions within WUA. The geospatial analysis methods of Average Nearest Neighbour (ANN) and Kernel Density Estimation (KDE) were used to identify the spatial structure distribution of A-level tourist attractions. Constructing Weighted Network Analysis to measure the traffic access time between tourist attractions and traveler origin and further using Network Analysis to measure the traffic access time between different tourist attractions. The traffic access time results were spatially visualized using Inverse Distance Weight (IDW). The study results were as follows. (1) The spatial structure of A-level tourist attractions in WUA indicated a core-periphery distribution in general. All tourist attractions showed clustering characteristics of the spatial distribution pattern. The spatial clustering degree was highest for human tourist attractions and lowest for nature tourist attractions. (2) Traffic access time results exhibited significant centrality with Wuhan as the core and regional differences in WUA. The road traffic accessibility of human tourist attractions was better than that of natural tourist attractions. (3) The spatial distribution and road traffic accessibility of tourist attractions in WUA indicated a circle structure centered on Wuhan, which aligned with the general rule of regional development. The accessibility of the north-south direction was weaker than the east- west direction in WUA. (4) Human tourist attractions were mainly concentrated in urban areas with high connectivity and intensive road networks. But natural tourist attractions were separated from traveler origin and other different tourist attractions. Most were in mountainous and hilly areas with poor accessibility, which could attract more tourists with better road networks and traffic infrastructure.

Urban environmental pollution management is of great practical significance to achieving sustainable urban economic development. To improve the efficiency of urban environmental pollution management, we have established a big data technology framework for urban environmental pollution treatment. The relevant pollution data collected are used for targeted pollution treatment. The results show that the average efficiency of environmental pollution control in the whole province of China has increased from 33.67% to 63.67%, an increase of 46%. Among them, the efficiency of environmental pollution control in Guangdong has increased most significantly, with a relative position of 26.47%, which is at the top of the list. Inner Mongolia has the weakest increase in environmental pollution control efficiency, with an appreciation of 6.89% relative to its position, while the other 16 provinces and cities have little change in environmental pollution control efficiency. between 2010 and 2020, the urban pollution and environmental treatment costs that residents need to bear changed significantly, with fluctuations of around 30%.

Estimating the flow coefficient is a crucial hydrologic process that plays a significant role in flood forecasting, water resource planning, and flood control. Accurate prediction of the flow coefficient is essential to prevent flood-related losses, manage flood warning systems, and control water flow. This study aimed to predict the flow coefficient for a period of 19 years (2000-2019) in the Aksu River Sub-Basin in Turkey, using historical climatic data, including precipitation, temperature, and humidity, provided by The Turkish State of Meteorological Service (TSMS). The study utilized three different approaches, namely, the Adaptive Neural Fuzzy Inference System (ANFIS), Simple Membership function and fuzzy Rules Generation Technique (SMRGT), and Gaussian Process Regression (GPR), to predict the flow coefficient. The models were evaluated using several statistical tests, such as Root Mean Square Error (RMSE), Coefficient of Determination (R2), Mean Absolute Error (MAE), and Mean Square Error (MSE), to determine their accuracy. Based on the evaluation criteria, it is concluded that the Simple Membership Functions and Fuzzy Rules Generation Technique (SMRGT) model has superior flow coefficient estimation performance than the other models.

Resource cities are highly dependent on resource industries and have a single industrial structure, so how to adjust and optimize the industrial structure is of practical significance to the sustainable development of resource cities. This paper combines the principle of data envelopment analysis (DEA) and the principle of industrial layout optimization to evaluate and position the current situation of industrial structure in resource cities. Based on this study, the simulation dynamic simulation of the path optimization of sustainable industrial development is conducted through the study of the dynamics principle, and the realism and validity of the model are tested by combining it with the actual data to realize the prediction of sustainable industrial path development. The results show that: In the simulation dynamic simulation prediction, the scale of the resource industry in resource cities decreases by about 6%-8% in 2020, and its simulation prediction data and real data have high consistency, which verifies the effectiveness of industrial structure adjustment and optimization strategy. This paper studies the optimization and upgrading of industrial structure to promote the sustainable development of a resource-based city economy, narrow the gap between the economic development of east and west regions, promote urbanization, and improve inter- and intra-regional development imbalance.

The usage of stone columns is one of the best ways to accentuate the ground. minimize settlement and increase the soil's carrying capacity. In this study, stone columns with complete geogrid reinforcement built of recycled concrete aggregates were utilized. Soft clay soils have been strengthened in a variety of methods. The results indicated that the use of stone columns made of recycled concrete aggregates fully reinforced with geogrid resulted in a significant improvement in the BC of soils. Compared to natural soil, the use of stone and double columns reinforced with a geogrid network improved the BC of the soil by 9% with an increase in the percentage of improvement when using other patterns.

This paper applies big data technology to promote the innovative development of online subject education and improve students' self-learning efficiency to promote innovative management interaction in the education industry. In the design process, big data technology is used to mine and analyze massive educational data, combine the learning needs of online subjects, and provide technical support for six application levels of the online subject education system. Document transformation of education data is performed through the DCF mechanism, and the synchronization time slot is divided into a safe time slot and a reservation time slot. Then, the adaptive recommendation function is used to extract valuable information from behavioral data for personalized learning resource pushing. To verify the practical application effect of big data technology in the online subject education innovation system, the simulation analysis results show that after applying big data technology, the recommended resources preference of the education system is above 86%, the subject coverage rate is 90.48%, and the performance of test scores is improved by 17.5% relative to Class C. This shows that big data technology optimizes the application mode of online subject education and can provide students with better-quality educational resources.

Geopolymer (GP) has recently emerged as a new and environmentally friendly alternative to standard soil stabilization agents such as lime and Ordinary Portland Cement (OPC) to reduce environmental concerns. The addition of fibers to treated soil limits crack propagation, enhancing its strength even further. This study used high calcium class C fly ash (CFA) reacted with 10 M NaOH as a geopolymer (GP) binder to treat weak sand soil. Polypropylene (PP) fibers with a length of 4.5 mm were used as reinforcement in amounts ranging from 0.3 to 1.5%. Microstructure and unconfined compressive strength (UCS) testing were performed on the generated specimens. The study proved the benefits of fiber inclusion in improving the mechanical behavior of the treated weak soil. Superior strength characteristics were observed in GP- treated soil mixes with a binder content of 20% and an Activator/Binder (A/B) ratio of 0.4 reinforced with 1.5% PP fibers by weight, indicating that they can be used as a sustainable alternative to traditional binders in deep soil mixing applications.

Global economic growth is now increasingly conflicting with the sustainable development strategy. In the context of ecological environmental preservation and air pollution prevention and control, this paper probes into the regional differentiation in the influencing factors of clean renewable energy consumption. First and foremost, a brief analysis of the status quo of clean renewable consumption in China was outputted, grounded on data on the input and output of 30 provinces and cities nationwide from 2010 to 2020. Then, national and regional models are built respectively in virtue of differential GMM, systematic GMM, and bias-corrected LSDV methods. Furthermore, efforts were invested in dissecting the working mechanism of the influencing factors and verifying the previous prediction resulting in applying the Tobit regression method. For every 1% increase in the green finance index, the clean renewable energy consumption rises by 0.882 accordingly, said the regression analysis results. Last but not least, it was concluded that the development level of green finance, internet advance, and technological progress significantly positively affected clean renewable energy consumption. While the industrial structure, the degree of openness, and the level of urbanization represented by the proportion of the secondary industry play hardly-seen impact.

In the context of carbon peaks and carbon neutrality, the traditional senior logistics majors generally have high investment, high consumption, and difficulty in implementation in teaching. In this paper, multimedia technology is introduced into the teaching practice of higher vocational logistics majors. Guided by the learning theory of constructing contextual cognition and the educational idea of "learn skills from practice", multimedia demonstration, multimedia experience, multimedia interaction, multimedia assessment, and other forms of teaching are carried out in multimedia practical training through several teaching steps, such as multimedia simulation teaching design, teaching implementation, and effect evaluation. In the teaching assessment, the use of multimedia teaching can make 23.2% of the students proficient in warehouse management and the process of each operation, so 88.4% of the students have a good grasp of the knowledge points of logistics professional teaching. It shows that multimedia technology can, to a certain extent, effectively crack the phenomenon of high input, high consumption, and difficult implementation in the teaching of higher vocational logistics majors and enhance the teaching effect of logistics practical training.